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The user can search for elements in an associative array, and delete elements from the array. The following shows how multi-dimensional associative arrays can be simulated in standard AWK using concatenation and the built-in string-separator variable SUBSEP:
In computer science, an associative array, map, symbol table, or dictionary is an abstract data type that stores a collection of (key, value) pairs, such that each possible key appears at most once in the collection. In mathematical terms, an associative array is a function with finite domain. [1] It supports 'lookup', 'remove', and 'insert ...
The language extensively uses the string datatype, associative arrays (that is, arrays indexed by key strings), and regular expressions. While AWK has a limited intended application domain and was especially designed to support one-liner programs , the language is Turing-complete , and even the early Bell Labs users of AWK often wrote well ...
In addition to support for vectorized arithmetic and relational operations, these languages also vectorize common mathematical functions such as sine. For example, if x is an array, then y = sin (x) will result in an array y whose elements are sine of the corresponding elements of the array x. Vectorized index operations are also supported.
In some languages, however, array data types have the semantics of associative arrays, with indices of arbitrary type and dynamic element creation. This is the case in some scripting languages such as Awk and Lua , and of some array types provided by standard C++ libraries.
Associative containers (C++) B. Bidirectional map; C. Content-addressable memory; ... Comparison of programming languages (associative array) R. Retrieval Data Structure
In C++, associative containers are a group of class templates in the standard library of the C++ programming language that implement ordered associative arrays. [1] Being templates , they can be used to store arbitrary elements, such as integers or custom classes.
The disadvantage of association lists is that the time to search is O(), where n is the length of the list. [3] For large lists, this may be much slower than the times that can be obtained by representing an associative array as a binary search tree or as a hash table.